Study on lossless hyper-spectral image compression algorithm based on subsection invertible matrix transform to eliminate spectral redundancy
基于分段可逆矩阵变换的超光谱图像无损压缩算法

This paper presented a new algorithm based on subsection invertible matrix transform to eliminate spectral redundancy, and 2D-CDF (2, 2) DWT was used together to eliminate spatial redundancy. Its redundancy elimination effect is better than that of 3D-CDF (2, 2) DWT. The experimental results show that in lossless image compression applications the method is much better than JPEG-LS, WinZip, ARJ, DPCM, the research result of a research team of Chinese Academy of Sciences, NMST and MST. Using Canal test images of JPL laboratory as an example data set, on the average the compression ratio using this algorithm increases by 43%, 38%, 36%, 31%, 17%, 13%, and 10% respectively compared to the above algorithms. The algorithm presented in this paper has advantages in computing efficiency and hardware realization convenience.